UACE: Active acoustics to monitor fish stock: a case study in Lake Malawi 

• Day: June 16, Monday
    Location / Time: A. TERPSIHORI at 17:40-18:00
• Last minutes changes: Cancelled
• Session: 03. Advances in acoustic measurement systems: Technologies and applications
  Organiser(s): Alessandra Tesei, Matthew Schinault, Purnima Ratilal
  Chairperson(s): Matthew Schinault
• Lecture: Active acoustics to monitor fish stock: a case study in Lake Malawi 
  Paper ID: 2103
  Author(s): Roee Diamant, Ivan Lončar, Shlomi Dahan, Marijan Vonić, Yeshaiho Pewzner, Daud Kassam, Salim M'balaka, Nikola Mišković
  Presenter: Roee Diamant
  Abstract: Although it is generally recognized that fish are an ecologically and commercially important group, our current knowledge of fish occurrence, composition (diversity), abundance and behavior (e.g. migration) is limited to anecdotal sightings and reports, often from laypersons. In situ marine monitoring bridges this gap and allows us to track and monitor marine life. We present the design details of an active acoustic system that can be used to detect and estimate the biomass of shoals and individual fish. The system consists of an omnidirectional projector, a planner array of four hydrophones and a low-cost controller for real-time analysis. The system is mounted over an autonomous drifter that continuously maintains depth for 5 days and ascends to report any detections. Emitting a series of short pulses, allows the formation of a 3D map of time, distance and angle-of- arrival. The map is analyzed using clustering to find connected areas within the point cloud that meet the mobility and size constraints for the expected targets.\n\nThe system was tested in Lake Malawi/Niassa/Nyasa (LMNN). The LMNN is the third largest great lake in Africa with currently an estimated 800–1000 fish species, most of which are endemic. The fish population in the LMNN is experiencing severe degradation due to anthropogenic and climatic stressors. From this observation, there is a need to monitor the health status of the fish stocks by collecting data in the field. The proposed autonomous acoustic monitoring can serve as a sustainable technology to monitor fish stocks and replace the traditional invasive net-based methods. In the full paper, we describe the details of the acoustic detection algorithm as well as the mechanical design of the drifter and show the results of several experiments conducted at LMNN to demonstrate the system’s ability to detect and track small fish of 5 cm in length.
• Corresponding author: Prof Roee Diamant
  Affiliation: University of Haifa and University of Zagreb
  Country: Israel